Publications associées (7)

Building a Knowledge Graph of Chinese Kung Fu Masters From Heterogeneous Bilingual Data

Yumeng Hou, Lin Yuan

Various endeavours into semantic web technologies and ontology engineering have been made within the organisation of cultural data, facilitating public access to digital assets. Although models for conceptualising objects have reached a certain level of ma ...
2023

Crosslingual Topic Modeling with WikiPDA

Robert West, Tiziano Piccardi

We present Wikipedia-based Polyglot Dirichlet Allocation (WikiPDA), a crosslingual topic model that learns to represent Wikipedia articles written in any language as distributions over a common set of language-independent topics. It leverages the fact that ...
ASSOC COMPUTING MACHINERY2021

On Representation Learning for Scientific News Articles Using Heterogeneous Knowledge Graphs

Karl Aberer, Angeliki Romanou, Panagiotis Smeros

In the era of misinformation and information inflation, the credibility assessment of the produced news is of the essence. However, fact-checking can be challenging considering the limited references presented in the news. This challenge can be transcended ...
ASSOC COMPUTING MACHINERY2021

FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents

Jean-Philippe Thiran, Hazim Kemal Ekenel, Guillaume Jaume

We present a new dataset for form understanding in noisy scanned documents (FUNSD) that aims at extracting and structuring the textual content of forms. The dataset comprises 199 real, fully annotated, scanned forms. The documents are noisy and vary widely ...
IEEE2019

Automated Taxonomy Induction and its Applications

Amit Gupta

Machine-readable semantic knowledge in the form of taxonomies (i.e., a collection of is-a edges) has proved to be beneficial in an array of NLP tasks including inference, textual entailment, question answering and information extraction. Such widespread ut ...
EPFL2017

Comparing different acoustic modeling techniques for multilingual boosting

Hervé Bourlard, Petr Motlicek, Philip Neil Garner, John David Scott Dines, David Imseng

In this paper, we explore how different acoustic modeling techniques can benefit from data in languages other than the target language. We propose an algorithm to perform decision tree state clustering for the recently proposed Kullback-Leibler divergence ...
Idiap2013

Applying Multi- and Cross-Lingual Stochastic Phone Space Transformations to Non-Native Speech Recognition

Hervé Bourlard, Philip Neil Garner, John David Scott Dines, David Imseng

In the context of hybrid HMM/MLP Automatic Speech Recognition (ASR), this paper describes an investigation into a new type of stochastic phone space transformation, which maps "source" phone (or phone HMM state) posterior probabilities (as obtained at the ...
Ieee-Inst Electrical Electronics Engineers Inc2013

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